Deterministic and Entanglement-Efficient Preparation of Amplitude-Encoded Quantum Registers

TL;DR

This paper introduces a deterministic quantum state preparation algorithm that reduces entanglement and resource requirements, potentially improving fidelity on NISQ devices despite lower theoretical fidelity.

Contribution

The authors develop a nonvariational, entanglement-efficient state preparation method that decreases the number of entangling gates needed, especially for low entanglement states.

Findings

Fewer entangling gates than isometric decomposition for low entanglement states

Potential for higher actual fidelities on NISQ devices due to reduced decoherence

Effective for normal and log-normal distribution states

Abstract

Quantum computing promises to provide exponential speed-ups to certain classes of problems. In many such algorithms, a classical vector $\mathbf{b}$ is encoded in the amplitudes of a quantum state $\left |b \right >$. However, efficiently preparing $\left |b \right >$ is known to be a difficult problem because an arbitrary state of $Q$ qubits generally requires approximately $2^Q$ entangling gates, which results in significant decoherence on today's Noisy Intermediate Scale Quantum (NISQ) computers. We present a deterministic (nonvariational) algorithm that allows one to flexibly reduce the quantum resources required for state preparation in an entanglement efficient manner. Although this comes at the expense of reduced theoretical fidelity, actual fidelities on current NISQ computers might actually be higher due to reduced decoherence. We show this to be true for various cases of interest such as the normal and log-normal distributions. For low entanglement states, our algorithm can prepare states with more than an order of magnitude fewer entangling gates as compared to isometric decomposition.